The present invention relates generally to Magnetic Resonance Imaging (MRI) systems, and more particularly, to a method and system for improving image quality.
Magnetic Resonance Imaging (MRI) is a well-known medical procedure for obtaining detailed, one, two and three-dimensional images of patients, using the methodology of nuclear magnetic resonance (NMR). MRI is well suited to the visualization of soft tissues and is primarily used for diagnosing disease pathologies and internal injuries.
Typical MRI systems include a superconducting magnet capable of generating a strong, homogenous magnetic field around a patient or portion of the patient; a radio-frequency (RF) transmitter and receiver system, including transmitter and receiver coils, also surrounding or impinging upon a portion of the patient; a magnetic gradient coil system also surrounding a portion of the patient; and a computer processing/imaging system, receiving the signals from the receiver coil in the form of Fourier transforms and processing the signals into interpretable data, such as visual images.
The superconducting magnet is used in conjunction with a magnetic gradient coil assembly, which is temporally pulsed to generate a sequence of controlled gradients in the main magnetic field during an MRI data gathering sequence.
SENSE (SENSitivity Encoding) is a technique for reducing MRI data acquisition time using multiple surface coil arrays. Generally, it reduces acquisition time by increasing the step size between phase encoding lines of the Fourier transform or by reducing the field of view (FOV). If an object extends outside the reduced field of view, however, aliasing (or wrap-around) occurs in the phase encoding direction. The aliasing includes replications of the object (called aliased replicates) in the phase encoding direction. The spacing of the replications is inversely related to the step size between phase encoding lines of the Fourier transform. Using SENSE to reduce scan time therefore decreases the spacing between aliased replicates in the image. SENSE processing combines aliased multicoil images to remove the aliasing from the final image.
Aliasing can be removed from multicoil images because the aliased replicates (“overlaps”) have different coil weighting factors. The expected number of aliased replicates at each pixel is defined as the “overlap structure.”SENSE processing calculates an expected overlap structure and then uses (previously measured) surface coil receive B1 fields (“sensitivities”) to combine multicoil data to remove aliasing from the final image. Optimal SENSE image quality requires an accurate measurement of the coil sensitivities and a correct calculation of the overlap structure. Inaccuracies in coil sensitivities lead to uncorrected aliasing in the final image. Inaccuracies in the overlap calculation lead to either uncorrected aliasing or increased noise in the final image. Scan regions with low signal (“holes”) lead to degraded SENSE image quality because coil sensitivity is hard to measure accurately and attempts to unwrap noise aliasing increase noise in the final image.
The new technique should minimize aliasing degradation in SENSE images and should improve SENSE signal-to noise-ratio (SNR). The present invention is directed to these ends.